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Stock market movement forecast: A Systematic review
Expert systems with applications, 2020Achieving accurate stock market models can provide investors with tools for making better data-based decisions. These models can help traders to reduce investment risk and select the most profitable stocks.
Oscar Bustos, Alexandra Pomares-Quimbaya
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Forecasting Equicorrelations [PDF]
SSRN Electronic Journal, 2011 We study the out-of-sample forecasting performance of several time-series models of equicorrelation, which is the average pairwise correlation between a number of assets. Building on the existing Dynamic Conditional Correlation and Linear Dynamic Equicorrelation models, we propose a model that uses proxies for equicorrelation based on high-frequency ...
Adam E Clements +2 more
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SSRN Electronic Journal, 2006 This paper develops a set of time series models to provide short-term forecasts (6 to 18 months ahead) of international trade both at the global level and for selected regions. Our results compare favourably to other forecasts, notably by the International Monetary Fund, as measured by standard evaluation measures, such as the root mean square forecast
Keck, Alexander, Raubold, Alexander
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Deep learning framework to forecast electricity demand
Applied Energy, 2019The increasing world population and availability of energy hungry smart devices are major reasons for alarmingly high electricity consumption in the current times.
J. Bedi, Durga Toshniwal
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Macroeconomic forecasts and microeconomic forecasters [PDF]
Journal of Economic Behavior & Organization, 2002 In the presence of principal-agent problems, published macroeconomic forecasts by professional economists may not measure expectations. Forecasters may use their forecasts in order to manipulate beliefs about their ability. I test a cross-sectional implication of models of reputation and information-revelation.
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Monthly Weather Review, 1987
It is shown that it is possible to predict the skill of numerical weather forecasts - a quantity which is variable from day to day and region to region. This has been accomplished using as predictor the dispersion (measured by the average correlation) between members of an ensemble of forecasts started from five different analyses.
Eugenia Kalnay, Amnon Dalcher
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It is shown that it is possible to predict the skill of numerical weather forecasts - a quantity which is variable from day to day and region to region. This has been accomplished using as predictor the dispersion (measured by the average correlation) between members of an ensemble of forecasts started from five different analyses.
Eugenia Kalnay, Amnon Dalcher
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Different states of multi-block based forecast engine for price and load prediction
International Journal of Electrical Power & Energy Systems, 2019This work proposes different prediction models based on multi-block forecast engine for load and price forecast in electricity market. Due to high correlation of load and price signals, the density of this reaction can affect the demand curve and shift ...
Wei Gao +5 more
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Seasonal crop yield forecast: Methods, applications, and accuracies
Advances in Agronomy, 2019The perfect knowledge of yield before harvest has been a wish puzzling human being since the beginning of agriculture because seasonal forecast of crop yield plays a critical role in decision making for different stakeholders—from farmers to policy ...
B. Basso, Lin Liu
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Forecasting demographic forecasts
International Journal of Forecasting, 2014Abstract Consider the financial sustainability of public finances in the context of stochastic demographics. Such analyses have typically been made under the assumption that future demographic developments are deterministic. When stochastic demographics have been considered, the problems have been simplified by assuming that the decision makers in ...
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Forecasting Earnings Forecasts [PDF]
, 2013 We analyze earnings forecasts retrieved from the I/B/E/S database concerning 596 firms for the sample 1995 to 2011, with a specific focus on whether these earnings forecasts can be predicted from available data. Our main result is that earnings forecasts can be predicted quite accurately using publicly available information.
Bert de Bruijn, Philip Hans Franses
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